将数组添加到numpy数组 [英] Adding an array to a numpy array

问题描述

我想要一个看起来像这样的numpy数组:

I'd like to have a numpy array that looks something like this:

X = np.array([[10, 20], [20, 25], [30, 16], [40, 18], [50, 90], [60, 87]])

我目前有一些从firestore中检索到的字典值:

I currently have dictionary values that I retrieve from firestore:

doc_ref = db.collection('CPU Logs')
query_ref = doc_ref.where(u'testData', u'==', True).order_by(u'logId')
docs = query_ref.get()

我遍历它们并将键值分配给2个变量id和usage，然后再将它们添加到数组toAppend中:

I loop through them and assign the key values to 2 variables, id and usage, before adding them to an array toAppend:

for doc in docs:
    values = doc.to_dict()
    id = values['logId']
    usage = values['usage']
    toAppend = [id, usage]

如果id为10，用法为30，则

toAppend看起来类似于[10, 30].现在，我很难尝试将其添加到一个空的numpy数组中.我尝试插入:

toAppend would look something like [10, 30] if the id were 10 and the usage were 30. Now, I'm having trouble trying to add it to an empty numpy array. I've tried inserting:

X = np.array([])
for doc in docs:
    values = doc.to_dict()
    id = values['logId']
    usage = values['usage']
    toAppend = [id, usage]
    a = X.flatten()
    np.insert(a, [0,0], toAppend)

print(X)

以及附加:

np.append(X, toAppend)

但是两者似乎都不起作用，因为print语句仅打印出[].

But both don't seem to work, as the print statement just prints out [].

推荐答案

看看

Have a look at the docs for insert and flatten: They both return new arrays (copies). So you need to write

X = np.insert(a, [0, 0], toAppend)

，以便X包含扩展数组.我也不认为您需要前面的X.flatten().

in order for X to contain the extended array. I also don't think you need the preceding X.flatten().

您应该考虑只构建一个嵌套的list，最后只将其转换一次，而不是插入一个numpy数组(这很昂贵).

Instead of inserting into a numpy array (which is expensive), you should consider just building a nested list and only convert it once at the end.

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